5 Abstract 4 Abstract This thesis is an outcome of the European Space Agency (ESA) project on Hazard Assessment and Prediction Long-term Observation of Icelandic Volcanoes and Glaciers Using ENVISAT-ASAR and Other Radar Data (ID 142, Principal Investigator U. Münzer). It comprises the results of five scientific papers (four published, one submitted) on several aspects of ice-volcano interactions in Iceland from an observational point of view. This study was motivated by the lack of information on how remote sensing can actually contribute to monitoring and understanding subglacial volcanoes and their interaction with the overlying ice cover. For example, no continuous monitoring of the Icelandic subglacial volcanoes utilizing any kind of satellite images has been conducted so far. The ice cover across subglacial volcanoes is influenced by several processes of the underlying volcano. The increased geothermal heat flux leads to temperate conditions everywhere at the glacier bed. Therefore, sliding is an important mechanism in the glacier dynamics of these glaciers. Also, the generation of large amounts of subglacial melt water during volcanic activity is the reason for jökulhaups (glacial torrent) and evolution of extensive subglacial tunnel systems (melt water drainage). In case of subaerial eruptions, glaciers are influenced by ash fall, which reduces the albedo at their surface and thus control the mass balance of the ice cover. In addition, the variable loading controlled by glacier mass balance has an effect on the volcanic activity itself. In this thesis, several approaches are documented which analyse some of the important interactions between subglacial volcanoes and their ice cover by remote sensing techniques. It was found that glacier mass-balance parameters, ice-dynamics, and subglacial volcanic processes can be detected by remote sensing analysis. One of the major problems for the investigation of temporal glacier development is the dectection of changes in extent and mass distribution. In this context, a combined analysis of optical (ASTER) and SAR (ENVISAT, ERS-2) data at Mýrdalsjökull test site was carried out which proved the potential to map the complete glacier outline and the temporal and spatial development of the transient snow line (TSL). Using this data, clear negative mass-balance conditions were determined for Mýrdalsjökull in Another approach for measuring accumulation rates was succesfully tested at the Vatnajökull test site. Using volcanic ash deposits of a subglacial eruption as time reference marker, it was possible to estimate accumulation rates by analysis of time sequential SAR (ENVISAT) backscatter data. In contrast to stake measurements, commonly used for accumulation measurements, this method provides areal coverage of the snow pack thickness. Influences of jökulhlaups on ice dynamics and the propagation of such floodwaves draining subglacially are currently a highly discussed topic. The new theory of sheet flow or coupled sheet and tunnel flow leading to widespread basal lubrification resulting in increased ice flow velocities could be confirmed by a study at Skeidarárjökull, a major outlet glacier of Vatnajökull ice cap. For investigation of ice dynamics, image-to-image cross-correlation of optical ASTER images proved very useful in absence of suitable SAR images for interferometric analysis. By using that technique, a mean annual surface velocity of Skeidarárjökull could be derived for the period 2001 until Compared to these values, significantly increased surface velocity was derived over the whole width of the glacier from an additional ASTER pair covering a jökulhlaup which drained under Skeidarárjökull.

6 Abstract 5 Knowledge about active subglacial geothermal areas and the subglacial tunnel system for melt water drainage is of great importance for hazard assessment purposes. Due to their characteristics, SAR data proved very useful for the study of the imprints of subglacial volcanic activity on a glacier surface. The ability to penetrate the upper layers of snow and firn enables the detection of buried topographic features of a glacier that are related to the underlying glacially- and fluvially-eroded bedrock or to subglacial volcanic activity. The analysis of a time series of SAR images (ERS-1/2, RADARSAT, JERS-1, ENVISAT) with special focus on identifying circular and linear depressions in the glacier surface of Mýrdalsjökull enabled the identification of subglacial geothermal heat sources and the connected subglacial drainage system. These data allowed a more precise identification of areas surrounding the glacier potentially endangered by a jökulhaup during a subglacial eruption and lead to a new, piecemeal caldera model of Katla volcano. This approach of investigating surface features by SAR time series analysis was transferred to Bardárbunga volcano under the northern parts of Vatnajökull, where seismic activity revealed unrest, to show its early-warning capabilities. The exact location of the corresponding active vent and therefore a potentially eruptive area could be detected in the SAR images leading to a precise prediction of surrounding regions prone to a jökulhlaup triggered by a possible future eruption at this location. The results of all these studies proved specialised remote sensing techniques to be very useful to identify and quantify a number of important processes connected to the intercation between subglacial volcanoes and the overlying ice cover. A multisensor and multitemporal approach is necessary for the quantification of mass exchange and monitoring of potential hazard areas. Planned and already launched satellite missions will provide the necessary data basis for the development of an efficient monitoring system, aiming at the detection of mass changes and potential hazards by subglacial volcanoes.

7 Introduction 6 1. Introduction There is the general trend in Earth Sciences nowadays, to deal with highly interdisciplinary problems and the theme ice-volcano interactions is clearly one that spans disciplines. The timeliness of investigating the interactions and hazardous effects of subglacial volcanic eruptions is also demonstrated by the recent formation of the International Association of Volcanology and Chemistry of the Earth's Interior (IAVCEI) working group of Volcano-Ice interactions. On a global level, volcanoes covered by glacier represent a major hazard by threatening lives, destroying property, capital and the environment on an enormous scale. Besides the usual volcanic hazards (lava flows, pyroclastic clouds, tephra fall, lightning etc.), the volcano-ice interaction leads to enormous meltwater torrents (jökulhlaup) or mudflows (lahar) that devastate large areas in the surroundings of the affected glacier. These indirect dangers can occur long after the eruption and may reach very far from the eruptive centre devastating regions that were thought not to be in danger from an eruptive hazard. An example of such an event is the eruption of Nevado del Ruiz in 1985 produced a series of pyroclastic flows and surges melting parts of the summit ice cap triggering lahars with a total volume of about 9 x 10 7 m 3 (Pierson et al., 1990; Thouret, 1990). More than people lost their lives in downstream areas up to 100 km away from the volcano summit. This thesis is mainly an outcome of the European Space Agency (ESA) project on Hazard Assessment and Prediction Long-term Observation of Icelandic Volcanoes and Glaciers Using ENVISAT-ASAR and Other Radar Data (ID 142), aiming to address questions relating to subglacial volcanic activity from an observational point of view. Direct observations of subglacial volcanoes are often difficult or even impossible to accomplish, therefore remote sensing seems a very promising tool allowing for the study of such large, remote and inaccessible areas. The use of remote sensing data enables a contribution to three crucial components in monitoring subglacial volcanoes: glaciology, volcanology, and hazard assessment. Seated atop the volcano, a glacier interacts with the volcanic processes and is an essential element to understand the complex system. Thus, an essential part of this thesis deals with the determination of glaciological parameters using remote sensing data. Gathering knowledge about the seasonal variations of a glacier or gradual retreat driven by a changing climate is of special interest, considering that seismicity of subglacial volcanoes in Iceland appears to be influenced by glacier loading and deloading throughout the year (Sigvaldason et al., 1992; Einarsson and Brandsdóttir, 2000). Indicators of subglacial volcanic activity can be identified indirectly by remote sensing analysis due to the ice cover. For example crustal deformations caused by magma movements interfere with ice flow of the overlying glacier, preventing a distinct classification of the signal. Nevertheless depressions in the glacier surface develop above subglacier geothermal areas due to the volume loss at the glacier bottom, triggered by ice melting from geothermal activity (Björnsson, 1975; Björnsson, 1988; Benn and Evans, 1998). A continuous satellite-based monitoring of the glacier surface morphology allows for detection of variations in the heat flux of the volcanic system and a better forecast of potential eruption locations. Moreover, the arrangement of identified subglacial geothermal areas enables insights on the structure of the volcanic edifice covered by glacier.

8 Introduction 7 Being the source for huge amounts of meltwater, the glacier further triggers the accompanying dangers (i.e., jökulhlaups, lahars) of subglacial volcanic eruptions and controls the flow direction of the flood likewise. In case of the thick Icelandic glaciers, meltwater produced by a subglacial eruption propagates subglacially from the eruption site to the glacier terminus (Björnsson, 1988). Therefore, exact knowledge about a potential eruption location and the origin of a floodwave is again crucial for the prediction of the potentially affected river catchment. It is possible to detect the preexisting subglacial drainage system, at least for parts of a glacier, by remote sensing analysis. The course of subglacial meltwater tunnels is indicated by halfpipe-shaped sinks on the glacier surface due to the viscoplastic nature of the ice cover. Meltwater tunnels serve as the initial transport network for the basal passage of melt water during a catastrophic jökulhlaup (Björnsson et al., 2001; Björnsson, 2002; Roberts, 2005) and must be considered for hazard zonation purposes. With knowledge of potential eruption sites and the pre-existing drainage system a precise prediction of peri-glacial regions prone to a devastating outburst flood accompanying a future eruption becomes possible. Iceland serves an ideal test area for investigating the potential and limits of monitoring ice-volcano interactions using remote sensing data. Approximately 11 % of the km² volcanic island is glaciated, consisting mainly of the four large plateau glaciers Vatnajökull (8.100 km²), Langjökull (953 km²), Hofsjökull (925 km²) and Mýrdalsjökull (586 km²) (Björnsson, 1979; Saemundsson, 1979; Sigurdsson, 1998; Adalgeirsdóttir, 2003; Jaenicke et al., 2006). The huge ice masses of these glaciers cover several volcanic systems with central volcanoes, crater chains, and fissures (Björnsson and Einarsson, 1990; Thordarson and Larsen, 2007). The high activity and production rate of the Icelandic volcanoes results from superposition of the spreading plate boundary of the Mid Atlantic Ridge (MAR) over the Iceland mantle plume (e.g., Vink, 1984; Wolfe et al., 1997; Shen et al., 2002; Thordarson and Larsen, 2007). The so-called Neovolcanic Zone (NVZ), the surface expression of the active spreading and plate growth crosses Iceland roughly from Southwest to Northeast with different branches, indicated by the distribution and arrangement of the active volcanic centers (Fig. 1). This thesis focuses on the two test sites Mýrdalsjökull and western Vatnajökull, covering several of Iceland s most active volcanoes. These ice caps were continuously imaged by ENVISAT-ASAR acquisitions throughout this thesis. Furthermore a ground network of artificial corner reflectors installed at Mýrdalsjökull (1995) and Vatnajökull (1997) in the periglacial areas of the two test sites support SAR data processing. The Katla volcanic system, overlain by Mýrdalsjökull ice cap, comprises an approximately 100 km² caldera, connected to an 80 km wide SW-NE trending fissure swarm (Jakobsson, 1979; Björnsson et al., 2000) (Fig. 1). The Katla volcanic rock series comprises two end-members which are Fe-Ti transitional-alkali basalts and mildly alkalic rhyolithes (Lacasse et al., 2006). On average two eruptions have occurred within the Katla system every century during the last 1100 years with minor subglacial events occurring in 1955 and 1999; whereas the peak rate of melt water discharge during the last major Katla eruption in 1918 was estimated as m³/s (Tómasson, 1996; Larsen, 2000; Sigurdsson et al., 2000; Soosalu et al., 2006). With an expanse of approximately km² Vatnajökull is the largest Icelandic and even European glacier. Results of this thesis focus on the two subglacial volcanic systems under its western part, namely Grímsvötn and Bárdarbunga. The Grímsvötn volcanic system shows the highest eruption frequency of all subglacial volcanoes beneath Vatnajökull with about 70 eruptions in historical time (Thordarson and Larsen,

9 Introduction ). The 62 km² caldera of the central volcano is situated in the central part of western Vatnajökull (Fig. 1). Due to ice cover, eruptions of Grímsvötn are phreatomagmatic and effects of the most recent Grímsvötn eruption which occurred from 1 6 November 2004, are presented here. The second most active volcano beneath Vatnajökull is the Bárdarbunga volcanic system. At least 23 eruptions are attributed to this system in historical time (Thordarson and Larsen, 2007). Bárdarbunga is a large volcanic edifice girding an 80 km 2 large caldera sited in the northern part of western Vatnajökull (Björnsson and Einarsson, 1990). Recent efforts have been directed to this area, as the northern flanks of Bárdarbunga show signs of unrest (i.e., increased seismic activity and sporadic heat flux) since end of NVZ WVZ EVZ B G K Figure 1: ENVISAT-ASAR wide swath image (30/12/2006) covering Iceland almost completely. Glaciated areas appear black (low backscatter intensity due to high water content of the snow cover at lower elevations) and light grey (dry snow cover at higher elevations leads to volume scattering and therefore high backscatter values). The course of the Neovolcanic Zone is indicated by the location of central volcanoes (reddish polygons) and their adjacent fissure swarms (yellow polygons). The different branches of the Neovolcanic Zone are the West Volcanic Zone (WVZ), the East Volcanic Zone (EVZ), and the North Volcanic Zone (NVZ). The green rectangle shows the Mýrdalsjökull test site with the Katla (K) volcano, the blue rectangle outlines the Vatnajökull test site with the volcanoes Bárdarbunga (B) and Grímsvötn (G).

10 Principles of SAR remote sensing 9 2. Principles of SAR remote sensing This section serves a short introduction to the remote sensing techniques utilised in this thesis. It is based on manuals and textbooks like Henderson and Lewis (1998), Lillesand and Kiefer (2004), and Ulaby et al. (1982) where additional and more technical information about SAR and optical remote sensing can be found. The main part of the results were achieved using Synthetic Aperture Radar (SAR) remote sensing, an important tool in light of the fact that Icelandic weather conditions and its proximity to the arctic circle hinder the use of other remote sensing tools. Radar is an acronym for Radio Detection and Ranging. It is an active sensor, transmitting a signal of electromagnetic energy, illuminating the terrain, and recording or measuring the response returned from the target or surface. Imaging radars are generally operating in the microwave region of the electromagnetic spectrum, including wavelengths from 1 mm to 1 meter (Fig. 2). Compared to passive optical sensors, mainly operating in the visible and infrared spectrum. Radar imaging has quite different characteristics due to the longer wavelength and active generation of microwave pulses illuminating the ground target. This enables continuous image acquisition independent from cloud cover and day light. Figure 2: Electromagnetic spectrum showing the microwave range and the respective radar bands. (http://www.asf.alaska.edu/reference/html/7_4_3 _2.html).

11 Principles of SAR remote sensing SAR geometry Radar is basically a distance measuring method, utilising the two-way travel time of an emitted microwave pulse between the antenna and various ground targets. Therefore radar has to be side-looking, otherwise objects with equal distance to the left and to the right of the sensor would give reflections at the same point in time and could not be distinguished. These SAR inherent recording parameters lead to some important terminologies and distortional effects which are described in the following. Figure 3 illustrates a simplified geometry of a side-looking radar sensor. The footprint illuminated by the microwave pulse is called radar swath. The swath width is controlled by the look angle (θ). Azimuth direction refers to the alongtrack dimension parallel to the flight direction, whereas the range direction describes the dimension perpendicular to the sensor path. According to the Figure 3: Simplified geometry of a side looking radar sensor. (Roth, 2001) distance from the flight path (nadir line) the radar swath is subdivided into near range and far range. As radar measures how far objects are from the sensor, distances are recorded in slant range along an imaginary line between the radar antenna and the target. Ground range is the perpendicular distance from the platform ground track to an illuminated object. Another important factor is the incidence angle which describes the angle between the incident radar beam and the ground surface assuming no topography. The term local incidence angle is used for the angle between the radar beam and the normal to the surface at a particular point. Incidence angle and local incidence angle are only equal over flat terrain respectively.

12 Principles of SAR remote sensing 11 The side-looking geometry also causes some distortions in radar images especially in mountainous areas known as layover, foreshortening, and shadow. These geometric distortions depend mainly on the relation between terrain slope and the look angle of the radar beam. Since the radar pulse is a emitted radially, equal travel times to ground objects are located on a circle centred at the sensor. As a result, objects with different distances on the ground may have the same distance from the satellite sensor. b c Figure 4: Distortions caused by the radar inherent side-looking geometry. Layover (a) results in a reversion of the terrain geometry. Foreshortening (b) causes compression of slopes facing towards the sensor. Points in the shadow (c) of an object are not visible in the radar image. (Roth, 2001) Figure 4a illustrates the layover effect. The mountain top (b) is closer to the sensor than the foot of the mountain (a). Therefore the signal of the mountain top (b) reaches the sensor before the reflection of the foot of the mountain resulting in layover of the terrain geometry in the slant range image. Generally, layover zones, facing radar illumination, appear as bright features in the image. The ambiguities in these zones can not be resolved due to the representation of several points on the ground by one single point in the image. In figure 4b the ground distance of the mountain slope is much larger than the recorded distance in the slant range geometry, because the top of the mountain is again relatively close to the sensor. This effect is called foreshortening. Foreshortening is obvious in radar images of mountainous areas, where the mountains seem to lean towards the sensor. The ambiguities of this range compression of the radiometric information backscattered from foreslope areas can be corrected by means of rectification procedures which use topographic information. The shadow effect (Fig. 4c) is caused by slopes facing away from the sensor with an angle that is steeper than the sensor look angle. Therefore such areas cannot be reached by the

13 Principles of SAR remote sensing 12 radar signal and appear dark (zero signal) in the image. Further, the radar shadows of two objects of the same height are longer in the far range than in the near range of an image. 2.2 SAR resolution A radar imaging system is characterised by its resolution in azimuth (along-track) and range (across-track) direction. Range resolution in a radar image is mainly controlled by the bandwidth of the emitted microwave pulse. To improve range resolution, pulse duration (τ) should be as short as possible. This would lead to a higher pulse repetition frequency allowing for distinction between more closely spaced objects. However, it is also crucial to transmit enough energy in a pulse to enable the detection of the reflected signals. If the pulse is shortened, its amplitude must be increased to keep the same total energy in the pulse. Technically this is achieved by frequency modulation of the emitted pulses (chirped pulse). Instead of a short pulse with a constant frequency, a long pulse is emitted with a modulated frequency. The frequency modulation must be processed after reception to focus the pulse to a much shorter value. The slant range resolution (r r ) of a radar system and the ground range resolution (r g ), which is the projection of the former to the ground is given by: and c = propagation velocity θ = look angle r r = r g = cτ 2 cτ 2 sin θ The azimuth resolution describes the ability of an imaging radar to separate two closely spaced targets in the direction parallel to the motion of the sensor. For a real aperture radar the resolution along track (azimuth resolution r a ) depends on the antenna beamwidth and the distance between the sensor and the observed surface and is given by: λ ra = r L r = distance between antenna and target λ = wavelength L = antenna length As height and therefore the distance to the target is fixed for satellite based imaging radars, a better resolution can only be achieved by increasing the antenna length. However, assuming a satellite height of about 800 km (like ENVISAT) equipped with a c-band radar (λ = 5.6 cm), an antenna length of 3 km would be required to obtain a 10 m azimuth resolution. Obviously this limits the usability of conventional radar and is overcome by a synthetic array approach. A Synthetic Aperture Radar (SAR) utilizes the motion of the sensor to simulate a long antenna (Fig. 5). The received signals from subsequent antenna positions are coherently recorded and then added in a processor,

14 Principles of SAR remote sensing 13 using the Doppler principle, to synthesize a long antenna array. With this technique, the 10 meter long ASAR antenna onboard the ENVISAT satellite achieves an azimuth resolution (single look) of about 4.8 m (Rosich et al. 2003). Figure 5: Simplified sketch of the SAR principle. (http://envisat.esa.int/object/index.cfm?fobjectid=3772& contentid=3829) 2.3 Interaction with target The SAR amplitude image provides information on the portion of the transmitted energy that is reflected back to the antenna from the illuminated surface. Darker areas in an amplitude image represent low backscatter, brighter areas indicate high backscatter. Generally two types of scattering mechanisms are possible: reflection at the surface which is called surface scattering while scattering inside the illuminated medium is called volume scattering. The main factors controlling the microwave interaction with the surface are roughness, geometric shape and dielectric properties of the target. Figure 6: Reflections from three different surface characteristics. (http://www.asf.alaska.edu/reference/general/scisaru serguide.pdf)

15 Principles of SAR remote sensing 14 Surface roughness is considered the main factor affecting radar backscattering. A rough surface (Fig. 6 B) will create much more backscatter to the sensor than a smooth surface which acts like a specular reflector (Fig. 6 A). There most of the energy is reflected away from the incoming direction. The Rayleigh criterion defines the classification of a surface depending on the wavelength of the sensor and is written as: and λ h > for a rough surface 8cosθ λ h < for a smooth surface 8cosθ h = mean height of surface variations λ = wavelength of the sensor θ = incidence angle Objects with a special shape can act like corner reflectors (Fig. 6 C) creating a double bounce reflection. This leads to punctually very high backscatter values in the image making such points easily identifiable. Artificial corner reflectors taking advantage of this principle. For example the two test sites of this thesis Mýrdals- and Vatnajökull were equipped with a network of artificial corner reflectors in the 1990 s (10 around each glacier, 5 oriented towards ascending and 5 oriented towards descending orbits respectively) to enable a fast and accurate geocoding of acquired SAR images. Another important factor controlling radar backscatter is the dielectric properties of the illuminated material. The complex dielectric constant (ε) is the principal description of the material s response to an electric field. It consists of two parts (permittivity and conductivity) that are both highly dependent on the moisture content of the illuminated material. In the microwave region, most natural materials have a dielectric constant between 3 and 8, under dry conditions, whereas water has a high dielectric constant of 80. As a result, a change in moisture content generally produces a significant change of the dielectric properties of natural materials. This means, that increasing moisture is associated with an increased radar reflectivity. In contrast to that, the penetration depth of electromagnetic waves in an object is an inverse function of water content. This means that dry materials tend to act as volume scatterers, while materials with increased moisture content acts as a surface scatterer. The amount of reflectivity recorded in a SAR image is also dependent on the sensor parameters (e.g. radar wavelength, viewing geometry, polarisation). As the sensor characteristics are known values, SAR amplitude images can be corrected to give the average reflectivity induced only by the properties of the scatterer. These calibrated images therefore denote the radar backscattering coefficient (σ 0 ) expressed in the logarithmic unit decibels. For snow and glacier ice which are mainly observed in this thesis the main factors controlling backscattering at SAR frequencies are: the liquid water content, the surface roughness (wet snow and glacier ice), internal interfaces, ice inclusions and grain size (dry or refrozen snow)

16 Principles of SAR remote sensing 15 Generally these factors are strongly influenced by seasonal variations. During the winter half, when the glacier is covered by dry snow, the SAR signal penetrates into this layer due to its small dielectric constant. Frozen ice pipes, ice lenses and internal interfaces in the snowpack result in high backscatter from the volume and therefore a bright appearance in the SAR image. When the snow gets wet in spring, σ 0 drops significantly. Surface scattering at the air/snow boundary is the dominant scattering mechanism where most of the incoming signal is reflected away from the sensor leading to dark appearance in the SAR image. In areas where bare ice is exposed on a glacier σ 0 is affected by the roughness and melting condition of the ice surface. In spring, when wet snow covers the ice, the signal originates again from the snow surface and σ 0 is low. The maximum of σ 0 on the ice surfaces in summer can be explained by the increased roughness during the melt period caused by crevasses or incised meltwater channels. Several examples and explanations of the different scattering mechanisms and, therefore, changing appearance of the test sites Mýrdals- and Vatnajökull can be found in paper 1, 2 and 4 of this thesis.

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